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This Week in Neo4j - 15th September 2018

This week we have recommendations with Personalized PageRank, Solving the bucket-filling problem, Deep Text Understanding, a new GraphQL book, Thinking in Graphs for security, and more!

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This Week in Neo4j - 15th September 2018

  1. 1. This Week in Neo4j
  2. 2. Developer Relations Engineer at Neo4j 2
  3. 3. The week's graph database news in one handy slide deck! Find the archive at
  4. 4. Learn more about Scott
  5. 5. This week Jeff Morris presented a webinar about Neo4j Bloom. Jeff explains why graph visualization is such an important tool for business users and then describes the features that Neo4j Bloom has to offer, such as near natural language search and code free graph changes. Watch the webinar
  6. 6. Tomaz Bratanic has written a blog post explaining how to use the Personalized PageRank algorithm. Tomaz goes through a worked example showing how to build an article recommender system that finds the best articles or papers for a keyword given the context of the researcher asking the question. Read the blog post
  7. 7. Vince Bickers explains how to solve the bucket-filling problem by creating a state machine where each state is a node, and transitions between states are relationships. He shows how to create the state machine using various Cypher queries and shows how to find all possible solutions for the problem using the shortest path algorithm. Read the blog post
  8. 8. Michael Hunger has written a pseudo blog post in response to a question on the Neo4j forum about Virtual Nodes and Relationships. In the post Michael explains why they’re useful and how they're already being used in the APOC and Graph Algorithms libraries. Read the article
  9. 9. Dinis Cruz shared the slides from his keynote, Thinking in Graphs, at the Open Security Summit 2018. Dinis covers various graphs in the security field, including threat modelling, and shows some of the work he's been doing to analyse security issues in Neo4j. Download the slides
  10. 10. Dr. Vlasta Kůs and Dr. Alessandro Negro have written a blog post titled Deep text understanding combining Graph Models, Named Entity Recognition and Word2Vec, in which they use GraphAware NLP to build a graph based of named entities from a Wikipedia dataset. Read the blog post